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Artificial intelligence in pharmacy practice: Attitude and willingness of the community pharmacists and the barriers for its implementation.
Jarab, Anan S; Al-Qerem, Walid; Alzoubi, Karem H; Obeidat, Haneen; Abu Heshmeh, Shrouq; Mukattash, Tareq L; Naser, Yara A; Al-Azayzih, Ahmad.
Afiliación
  • Jarab AS; Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology. P.O. Box 3030. Irbid 22110, Jordan.
  • Al-Qerem W; College of Pharmacy, AL Ain University, Abu Dhabi, United Arab Emirates.
  • Alzoubi KH; Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan. P.O. Box 130, Amman 11733, Jordan.
  • Obeidat H; Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah, UAE.
  • Abu Heshmeh S; Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
  • Mukattash TL; Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology. P.O. Box 3030. Irbid 22110, Jordan.
  • Naser YA; Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology. P.O. Box 3030. Irbid 22110, Jordan.
  • Al-Azayzih A; Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology. P.O. Box 3030. Irbid 22110, Jordan.
Saudi Pharm J ; 31(8): 101700, 2023 Aug.
Article en En | MEDLINE | ID: mdl-37555012
ABSTRACT

Background:

Artificial intelligence (AI) is the capacity of machines to perform tasks that ordinarily require human intelligence. AI can be utilized in various pharmaceutical applications with less time and cost.

Objectives:

To evaluate community pharmacists' willingness and attitudes towards the adoption of AI technology at pharmacy settings, and the barriers that hinder AI implementation.

Methods:

This cross-sectional study was conducted among community pharmacists in Jordan using an online-based questionnaire. In addition to socio-demographics, the survey assessed pharmacists' willingness, attitudes, and barriers to AI adoption in pharmacy. Binary logistic regression was conducted to find the variables that are independently associated with willingness and attitude towards AI implementation.

Results:

The present study enrolled 401 pharmacist participants. The median age was 30 (29-33) years. Most of the pharmacists were females (66.6%), had bachelor's degree of pharmacy (56.1%), had low-income (54.6%), and had one to five years of experience (35.9%). The pharmacists showed good willingness and attitude towards AI implementation at pharmacy (n = 401). The most common barriers to AI were lack of AI-related software and hardware (79.2%), the need for human supervision (76.4%), and the high running cost of AI (74.6%). Longer weekly working hours (attitude OR = 1.072, 95% C.I (1.040-1.104), P < 0.001, willingness OR = 1.069, 95% Cl. 1.039-1.009, P-value = 0.011), and higher knowledge of AI applications (attitude OR = 1.697, 95%Cl (1.327-2.170), willingness OR = 1.790, 95%Cl. (1.396-2.297), P-value < 0.001 for both) were significantly associated with better willingness and attitude towards AI, whereas greater years of experience (OR = 20.859, 95% Cl (5.241-83.017), P-value < 0.001) were associated with higher willingness. In contrast, pharmacists with high income (OR = 0.382, 95% Cl. (0.183-0.795), P-value = 0.010), and those with<10 visitors (OR = 0.172, 95% Cl. (0.035-0.838), P-value = 0.029) or 31-50 visitors daily (OR = 0.392, 95% Cl. (0.162-0.944), P-value = 0.037) had less willingness to adopt AI.

Conclusions:

Despite the pharmacists' positive willingness and attitudes toward AI, several barriers were identified, highlighting the importance of providing educational and training programs to improve pharmacists' knowledge of AI, as well as ensuring adequate funding support to overcome the issue of AI high operating costs.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Saudi Pharm J Año: 2023 Tipo del documento: Article País de afiliación: Jordania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Saudi Pharm J Año: 2023 Tipo del documento: Article País de afiliación: Jordania
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